Gender Parity and Youth Employment in Nigerian Tertiary Institutions: A Study of Auchi Polytechnic, Auchi, Edo State, Nigeria
Bibliographic record
Abstract
In recent times, gender issues have continued to be at the centre stage of every political discourse in many regional, national and international fora. Although much has been written on gender as an academic discipline, gender parity and youth employment in Nigerian tertiary institutions is yet to be given the desired attention. Thus, women employment cannot be ignored even when employment pattern in Africa still favours men more than women. This paper investigates gender parity and youth employment in Nigerian tertiary institutions with particular focus on recruitment of young men and women into academic positions in Auchi Polytechnic, Auchi. To achieve the purpose of the study, a sample of 325 academic staff was selected for the research. The study tested a hypothesis of no relationship between gender parity and youth employment in Nigerian tertiary institutions using a statistical tool called t- test statistic with the help of statistical software known as SPSS version 16.0. The t-statistic analysis showed that there is a significant relationship between gender parity and youth employment among academic staff of Auchi Polytechnic, Auchi since tcal (87:41)> ttab (2:31) at 5% critical level. It concluded that there is gender imbalance in the employment of academic staff as male youth are more in employment than female youth in Nigerian tertiary institutions. The paper recommends among others the need for government to enshrine into law gender equality in terms of employment opportunities for all qualified citizens in Nigeria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".